Tom Bacon hears lessons from Wyndnam Destination Network, which advises that revenue managers use business language, common metrics and storytelling to communicate more effectively
It is not unusual for a revenue management model, or any sophisticated optimisation model founded on big data, to recommend unintuitive actions as highlighted below:
Don’t sell the seat at a discount even though there are 20 empty seats
Do not match the low corporate fare offered by a competitor to a major client
Do not raise fares despite a consistent 90% load factor
Do not lower fares despite a consistent 65% load factor
Most of the time, these actions are based on multi-level statistical analysis, trading off opportunity costs and actual costs, comparison of the probability of success across a range of solutions. Communicating such recommendations to the rest of the organisation, and to high-level executives, remains a key challenge for RM. Sales needs to know why RM is putting its biggest client at risk. Senior management needs to understand why financial losses pile up despite high load factors on a particular flight or market.
At the EyeforTravel Smart Analytics conference in Atlanta, Kelly McGuire, Vice President, Advanced Analytics of Wyndham Destination Network, outlined some communication tips for RM organisations faced with a puzzle. She offered three suggestions namely to use business language, employ common metrics (focus on profitability and cite analogies (tell a story).
Let us see how this would work with some of the common, somewhat puzzling, RM actions.
PUZZLE 1: 65% load factor is optimal. Don’t lower fares
Acceptance of low load factors remains one of the more challenging RM actions. Why not sell more seats? Using McGuire’s guide, I would offer:
1. Business Language: Based on our analysis, offering a lower fare would cause existing customers to pay less. Expected dilution is not forecast to be offset by enough new passengers to be net positive. We are already offering a fare structure that includes low fares; few passengers are buying the lowest, heavily restricted fares but instead most are purchasing higher, less restricted fares.
2. Common Metrics: A lower $10 per passenger would require 12 more passengers to breakeven on revenue, or a 15% increase in traffic – not something that is likely to happen in this tiny, business market. The market is more profitable by focusing on high fare traffic.
3. Analogy: The market is essentially a niche market – we fly it to accommodate high fare demand. This is our ‘Tiffany’s’ or ‘Lexus’. We shouldn’t discount this niche product.
PUZZLE 2: We can’t raise fares further even though we are consistently hitting a 95% load factor
The converse to the first unintuitive result is, on the surface, similarly illogical. Why can’t you get another $1-$5 out of passengers if you are filling the plane at existing fares?
1. Business Language: This market is full of the very lowest fares – we are competing on price alone here against multiple airlines with better schedules than we have. If we are not competitive with our competitors, even by $1-$5, we will lose passengers. Part of the reason for our high load factors is heavy reliance on non-refundable tickets (fully refundable business fares often experience higher no-show rates).
2. Common Metrics: A $5 fare increase on our lowest fares would be expected to reduce demand by over 20%.
3. Analogy: Our product in this market is a commodity, with price the main factor in customer decision-making.
PUZZLE 3: Rejecting a large customer’s request to match a competitor’s fare is appropriate
Another common problem for RM is dealing with sales on retention of large, demanding corporate customers.
1. Business Language: This large customer is one of many with a similar business profile and the fares it pays today are not out of line with its peers. We provide excellent service, something that no other carrier can match. Our experience is that:
a. Rumours of a lower fare offered by a competitor often can’t be backed up
b. Even if the bid is real, the customer ultimately decides to stay with us 75% of the time
2. Common Metrics: Dropping the fare will reduce revenue by a known $100,000 for this customer alone but if we were to do this for all customers in the same situation, the impact would grow to more than $1 million. Based on the 75% likelihood that we’ll retain the customer anyway we expect to lose much less by holding the line.
3. Analogy: Granting such an exception to standard pricing undermines the whole structure. Our corporate pricing structure is currently established based on measurable results; current pricing for this customer fits right into the existing framework. A request to give an exception to this customer threatens the whole structure.
Sometimes, perhaps often, RM recommends an action that is not obvious on the surface or not obvious given the different perspectives, different metrics and different incentives across a broad organisation. RM needs to listen carefully to objections from the rest of the organisation and respond in easy-to-understand business terms.
Tom Bacon has been in the business for 25 years, as an airline veteran and industry consultant in revenue optimisation. He leads audit teams for airline commercial activities including revenue management, scheduling and fleet planning. Questions? Email Tom or visit his website